get_analytics_group_models

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds that it's paginated and gated (returns 403 on non-Enterprise plans), which is helpful but doesn't disclose additional traits like rate limits or response structure. Adequate but not excessive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences covering purpose, usage guidance, and access restriction. No redundancy, front-loaded with key information, and every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (31 parameters, output schema exists), the description covers purpose, alternatives, and gating. It could briefly mention pagination behavior or output shape, but output schema handles the latter. Slightly incomplete on pagination details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% coverage with descriptions for each parameter. The tool description does not add any parameter-level meaning beyond what the schema provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves a paginated per-model breakdown with specific metrics (total_groups, group_count, models array). It distinguishes from related tools like get_token_analytics and get_cost_analytics, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use for comparing model cost, popularity, and efficiency, and directs to alternatives for time-series trends. Also notes the Enterprise-gated restriction, setting clear expectations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.